Meta

Bateman’s principles are conceptually quite simple, but form the basis of our understanding of sexual selection across the animal kingdom. First proposed in 1948, Bateman’s three principles posit that sexual selection is more intense in males than in females for three reasons:

1) males show more variability in the number of mates they have (mating success);
2) males show more variability in the number of offspring they have (reproductive success);
3) the slope of the relationship between mating and reproductive success is steeper in males;

Together, this summarises our basic view of sexual selection in the majority of sexually reproducing species – males that do well, do very well and we expect more intense sexual selection because of it.

Biased Traditions
Traditionally, most studies investigating these relationships have measured mating success by counting the number of females a male produces offspring with. This method is biased though, as it assumes that every mating results in offspring, which is unlikely to be true. Further, it assumes that every fertilisation produces an offspring, which ignores cases where embryos die before birth. Using offspring counts as a way to measure mating success might not be accurate but it is certainly more practical – behavioural observations of actual mating would be very time consuming and nearly impossible for some species. However, until now no study has attempted to quantify the importance of these biases in calculating and testing Bateman’s principles.

Carefully Observed
To address this issue, GEE researchers Dr Julie Collet and Dr Rebecca Dean, in collaboration with researchers at the University of Oxford, University of Queensland, Uppsala University and the University of East Anglia, investigated mating and reproductive success in Red Junglefowl (Gallus gallus). They recorded matings and collected all eggs laid from 13 groupings of 3 males and 4 females (mimicking natural conditions). They began by using classic techniques to estimate Bateman’s gradients – they inferred mating success from the number of females they sired an offspring with. They found twice as much variability in male mating success, and four times as much variance in male reproductive success (the actual number of offspring a male produced) compared with females. Mating success and reproductive success were strongly related – differences between individuals in mating success explained 57% of variance in reproductive success in males, but only 24% in females, and the slope of the relationship was steeper in males.

A Male Red Jungle Fowl

They then repeated their analysis but with a more accurate measure of mating success – the actual number of partners and matings observed. In this study, 30% of pairs that mated did not produce any offspring together and would be ignored by the traditional measure of ‘mating success’. Including these matings reduced the variability in mating success in both males and females. It also reduced the explanatory power of mating success – using this technique they found that variation in mating success actually explained 43% of variation in male reproductive success, and just 5% of variation in female reproductive success. This suggests that traditional methods for measuring Bateman’s principles are likely to be overestimating their importance and the extent of sexual selection on males.

Covarying Factors
Reproductive success is not just a product of how many mates you have. The fecundity of your mate is also a crucial factor, and in species where females mate with multiple males, your share of her offspring is also a key variable. The authors investigated whether these variables tend to be related and whether multivariate analyses that take them all into account better explain the overall reproductive success of a male. Their multivariate model explained the variance in male mating success better than the standard approach and found that mating success, paternity share and mate fecundity together are responsible for the variance in male reproductive success. The authors estimate that by ignoring these other factors, other studies may overestimate the Bateman gradient by as much as 150%!

This study shows the importance of investigating the biases we introduce into our science. These biases may sometimes be inevitable, if excluding them is extremely time consuming or difficult. But we must try to understand the influence of these biases in order to draw informed conclusions from our data. Here, GEE researchers demonstrate how using biased measures of mating success can cause scientists to overestimate the opportunity for sexual selection on males. This effect is likely to be largest for species which have small clutch sizes and in which sperm competition plays a key role. Where possible, studies investigating sexual selection should include accurate measures of mating success, and include other variables such as paternity share and mate fecundity in a multivariate approach in order to best understand Bateman’s principles and the relationship between mating and reproductive success in both sexes.

You’ve probably never given much consideration to why there are men and women. Or, more specifically, why there are two sexes, rather than one, three or 50. But this is a question that has been keeping some scientists awake at night for decades. Recent research in the department of Genetics, Evolution and Environment used mathematical models of evolution to investigate how the evolution of the two sexes was influenced by the inheritance patterns of the energy-producing organelle, mitochondria. The results of this model contradict previous work supporting the idea that inheritance of mitochondria through only one parent might explain the emergence of two sexes. The evolutionary dynamics of mitochondrial inheritance are more complex than previously thought.

Sexual reproduction is a beneficial thing, in evolutionary terms, but this benefit doesn’t depend upon there being different sexes, only on there being two individuals sharing their genes to produce an offspring. This system would also work with no sexes at all (everyone can mate with everyone), or with many sexes. In fact, two is actually the worst number you could have picked – with two sexes any individual is limited to an available pool of mates just 50% of the population. With three sexes, this pool would increase to 66% of the population, with four 75%, and so on. So why have most sexually-reproducing species on settled on two sexes?

In a few previous GEE blog articles (see here and here), I have discussed the phenomenon known as ‘uniparental mitochondrial inheritance’ (UPI), in which mitochondria, organelles found in our cells that are responsible for generating energy, are inherited only through the maternal line – that is, you inherit all of your mitochondria from your mother and none from your father. UPI is found in many living things, although some species do things a bit differently and there are many different ways to achieve the same result. Work by GEE researcher Professor John Allen has previously shown that the mitochondria within egg cells in jellyfish, fruit flies and fish are largely inactive; this inactivity allows for a perfect ‘mitochondrial template’ to be passed on to the offspring and prevent the accumulation of mutations through the generations. Essentially, this is why aging isn’t heritable. It wouldn’t work to inactivate sperm mitochondria because they need so much energy for all that swimming, so if we did inherit mitochondria from our fathers they would probably be mutated. UPI is also thought to help evolution remove harmful mutations from the population and reduce conflict and promote coadpatation between the mitochondrial symbiont and its host cell.

So, UPI makes a lot of sense, evolutionarily, and some scientists think it might also explain why we have two sexes, as opposed to any other mating system. It’s important to be clear, when we talk about having two sexes we’re saying nothing about the external differences between the sexes (sexual dimorphism) observed in many multicellular organisms. We’re talking about the existence of two ‘mating types’, such that individuals cannot mate with members of the same type. Recent research by another group of GEE academics including Professor Andrew Pomiankowski, Dr Nick Lane and Professor Robert Seymour, investigated the evolution of UPI and in particular it’s relationship with the evolution of a two-sex mating system. We might expect a strong link between UPI and the existence of two sexes, since uniparental inheritance immediately generates differences between the two mating partners, and ensures that reproduction is not possible unless one member of each ‘type’ is present. Although UPI is often thought to have been a key driver in the evolution of mating types, there have been few investigations of what conditions are needed for the fitness benefits of UPI to actively drive the emergence of two mating types. So the authors developed a new mathematical model of mitochondrial inheritance and the evolution of UPI in a population where biparental inheritance (BPI) is the norm. They incorporated mitochondrial mutation (which might sometimes be selfish) and selection into the model, and included different mating types.

The model agreed with a great deal of previous work that indicates that UPI tends to increase fitness. It does so slowly, with selection acting cumulatively across many generations to remove less fit mitochondrial variants and increase fitness for UPI individuals. In a population of individuals where mitochondria is inherited biparentally, a new mutation causing UPI exists in a single individual. Slowly UPI improves the fitness of cells by reducing the number of mutated mitochondria they carry, and the UPI mutation might start to spread in the population. The problem is, as it spreads the benefits of UPI are inevitably leaked into the rest of the BPI population – UPI individuals mate with BPI individuals producing some BPI offspring who carry the fitter mitochondria from their UPI parent. This leaking of benefits means that the fitness benefits of UPI are frequency-dependent; the more common UPI becomes in a population, the less each UPI individual benefits from the reproductive strategy. This makes it hard for UPI to fully take over a population – their model tended instead to produce mixed populations with some UPI and some BPI individuals interbreeding.

Leaking of fit mitochondrial (blue) into BPI cells (a)

If the researchers included mating types in the model at the start of it’s evolutionary run, then UPI could become associated with specific mating types and in this situation, so long as mutation rates were high or each cell carried many mitochondria, UPI could spread to fixation in the population. But UPI itself was not able to alter the number or existence of mating types. The authors suggest that this may explain the continuum of UPI levels we observe in nature. For any given species, the occurrence of UPI will depend upon the evolutionary starting point, energetic demands, mutation rates and the selfish (or unselfish) nature of mutations.

Although most people never even consider why we have two sexes, male and female, the evolution of a two mating-type system is seemingly paradoxical and many theories and hypotheses have been proposed to explain it. One such explanation is that uniparental inheritance, which is critical for stabilising the mitochondria-cell symbiosis and preventing the accumulation of harmful mutations, may have driven the evolution of two sexes. However, mathematical modelling by scientists in GEE suggests this is not the case, and UPI more likely evolved after the two mating-type system emerged. In their model, although UPI initially spreads through populations, it’s fitness benefits are frequency-dependent, meaning it only rarely takes over an entire population. Populations in which all members inherit mitochondrial uniparentally are only possible when a mutation causing UPI becomes tighly linked to genes that determine mating type. The initial emergence of two mating types still requires an explanation independent from mitochondrial inheritance patterns.